MX2017008975A - Generacion de datos de sensor virtual para deteccion de receptores de bolardos. - Google Patents
Generacion de datos de sensor virtual para deteccion de receptores de bolardos.Info
- Publication number
- MX2017008975A MX2017008975A MX2017008975A MX2017008975A MX2017008975A MX 2017008975 A MX2017008975 A MX 2017008975A MX 2017008975 A MX2017008975 A MX 2017008975A MX 2017008975 A MX2017008975 A MX 2017008975A MX 2017008975 A MX2017008975 A MX 2017008975A
- Authority
- MX
- Mexico
- Prior art keywords
- sensor data
- virtual sensor
- ground truth
- virtual
- bollard
- Prior art date
Links
- 238000001514 detection method Methods 0.000 title 1
- 238000000034 method Methods 0.000 abstract 5
- 230000004888 barrier function Effects 0.000 abstract 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
- G08G1/165—Anti-collision systems for passive traffic, e.g. including static obstacles, trees
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/15—Vehicle, aircraft or watercraft design
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Evolutionary Computation (AREA)
- General Engineering & Computer Science (AREA)
- Software Systems (AREA)
- Computer Hardware Design (AREA)
- Geometry (AREA)
- Data Mining & Analysis (AREA)
- Transportation (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Mechanical Engineering (AREA)
- Medical Informatics (AREA)
- Automation & Control Theory (AREA)
- Computing Systems (AREA)
- Mathematical Physics (AREA)
- Traffic Control Systems (AREA)
- Measurement Of Velocity Or Position Using Acoustic Or Ultrasonic Waves (AREA)
Abstract
La descripción hace referencia a métodos, sistemas y aparatos para generación de datos de un sensor virtual y, de modo más particular, hace referencia a generación de datos de un sensor virtual para entrenamiento y análisis de modelos o algoritmos para detectar objetos u obstáculos, como receptores de bolardos. Un método para generar datos del sensor virtual incluye simular un entorno tridimensional (3D) que incluya uno o más objetos, como receptores de bolardo. El método incluye generar datos del sensor virtual para múltiples posiciones de uno o más sensores en el entorno 3D. El método incluye determinar la realidad virtual del terreno correspondiente a cada una de las múltiples posiciones. La realidad del terreno incluye información sobre al menos un receptor de bolardo en los datos del sensor. Por ejemplo, la realidad del terreno puede incluir una altura de al menos una de las barreras de estacionamiento. El método también incluye almacenar y asociar los datos del sensor virtual y la realidad virtual del terreno.
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US15/204,484 US20180011953A1 (en) | 2016-07-07 | 2016-07-07 | Virtual Sensor Data Generation for Bollard Receiver Detection |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| MX2017008975A true MX2017008975A (es) | 2018-01-08 |
Family
ID=59676808
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| MX2017008975A MX2017008975A (es) | 2016-07-07 | 2017-07-06 | Generacion de datos de sensor virtual para deteccion de receptores de bolardos. |
Country Status (6)
| Country | Link |
|---|---|
| US (1) | US20180011953A1 (es) |
| CN (1) | CN107589418A (es) |
| DE (1) | DE102017115197A1 (es) |
| GB (1) | GB2554148A (es) |
| MX (1) | MX2017008975A (es) |
| RU (1) | RU2017123627A (es) |
Families Citing this family (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9836895B1 (en) | 2015-06-19 | 2017-12-05 | Waymo Llc | Simulating virtual objects |
| CN109643125B (zh) * | 2016-06-28 | 2022-11-15 | 柯尼亚塔有限公司 | 用于训练自动驾驶***的逼真的3d虚拟世界创造与模拟 |
| WO2018017973A1 (en) * | 2016-07-22 | 2018-01-25 | Sri International | Computational analysis of observations for determination of feedback |
| JP6852790B2 (ja) * | 2017-06-23 | 2021-03-31 | 株式会社村田製作所 | 位置推定システム |
| WO2019069629A1 (ja) * | 2017-10-06 | 2019-04-11 | 富士フイルム株式会社 | 画像処理装置及び学習済みモデル |
| US10916074B2 (en) * | 2018-07-16 | 2021-02-09 | Ford Global Technologies, Llc | Vehicle wheel impact detection |
| WO2020140047A1 (en) * | 2018-12-28 | 2020-07-02 | Nvidia Corporation | Distance to obstacle detection in autonomous machine applications |
| CN109782908A (zh) * | 2018-12-29 | 2019-05-21 | 北京诺亦腾科技有限公司 | 一种在vr场景中模拟测量的方法及装置 |
| CN109815555B (zh) * | 2018-12-29 | 2023-04-18 | 百度在线网络技术（北京）有限公司 | 自动驾驶车辆的环境建模能力评估方法及*** |
| US11676429B2 (en) | 2019-09-04 | 2023-06-13 | Ford Global Technologies, Llc | Vehicle wheel impact detection and response |
| US11928399B1 (en) * | 2019-09-24 | 2024-03-12 | Zoox, Inc. | Simulating object occlusions |
| CN115200917B (zh) * | 2022-09-18 | 2022-12-06 | 江苏壹心智能科技有限公司 | 一种设备运行出厂检测用测试舱 |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102008001256A1 (de) * | 2008-04-18 | 2009-10-22 | Robert Bosch Gmbh | Verkehrsobjekt-Erkennungssystem, Verfahren zum Erkennen eines Verkehrsobjekts und Verfahren zum Einrichten eines Verkehrsobjekt-Erkennungssystems |
| DE102011050369A1 (de) * | 2011-05-16 | 2012-11-22 | Dr. Ing. H.C. F. Porsche Aktiengesellschaft | Simulationssystem für Fahrerassistenzsysteme |
| DE102013217430A1 (de) * | 2012-09-04 | 2014-03-06 | Magna Electronics, Inc. | Fahrerassistenzsystem für ein Kraftfahrzeug |
| KR101515496B1 (ko) * | 2013-06-12 | 2015-05-04 | 국민대학교산학협력단 | 가상현실에서 변동되는 장애물 정보를 반영한 무인 자동차의 자율 주행 시뮬레이션 시스템 |
-
2016
- 2016-07-07 US US15/204,484 patent/US20180011953A1/en not_active Abandoned
-
2017
- 2017-07-03 CN CN201710532534.2A patent/CN107589418A/zh active Pending
- 2017-07-05 RU RU2017123627A patent/RU2017123627A/ru not_active Application Discontinuation
- 2017-07-06 GB GB1710915.8A patent/GB2554148A/en not_active Withdrawn
- 2017-07-06 MX MX2017008975A patent/MX2017008975A/es unknown
- 2017-07-06 DE DE102017115197.4A patent/DE102017115197A1/de not_active Withdrawn
Also Published As
| Publication number | Publication date |
|---|---|
| RU2017123627A (ru) | 2019-01-09 |
| CN107589418A (zh) | 2018-01-16 |
| DE102017115197A1 (de) | 2018-01-11 |
| GB2554148A (en) | 2018-03-28 |
| GB201710915D0 (en) | 2017-08-23 |
| US20180011953A1 (en) | 2018-01-11 |
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